Overview

Dataset statistics

Number of variables10
Number of observations385500
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory29.4 MiB
Average record size in memory80.0 B

Variable types

Numeric10

Alerts

area[10] is highly overall correlated with area[9] and 2 other fieldsHigh correlation
area[9] is highly overall correlated with area[10] and 2 other fieldsHigh correlation
negpmax[10] is highly overall correlated with area[10] and 2 other fieldsHigh correlation
negpmax[11] is highly overall correlated with pmax[11]High correlation
pmax[10] is highly overall correlated with area[10] and 2 other fieldsHigh correlation
pmax[11] is highly overall correlated with negpmax[11]High correlation
negpmax[10] is highly skewed (γ1 = -330.2197187)Skewed
negpmax[11] is highly skewed (γ1 = -375.0891779)Skewed

Reproduction

Analysis started2024-01-24 23:04:41.045002
Analysis finished2024-01-24 23:04:59.996342
Duration18.95 seconds
Software versionydata-profiling vv4.6.3
Download configurationconfig.json

Variables

area[9]
Real number (ℝ)

HIGH CORRELATION 

Distinct383699
Distinct (%)99.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean7.843535
Minimum-2.207168
Maximum96.623736
Zeros0
Zeros (%)0.0%
Negative18
Negative (%)< 0.1%
Memory size2.9 MiB
2024-01-25T00:05:00.070599image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/

Quantile statistics

Minimum-2.207168
5-th percentile1.8978876
Q13.4622562
median5.7533383
Q39.3922916
95-th percentile23.284752
Maximum96.623736
Range98.830904
Interquartile range (IQR)5.9300354

Descriptive statistics

Standard deviation6.9405197
Coefficient of variation (CV)0.88487139
Kurtosis6.9614469
Mean7.843535
Median Absolute Deviation (MAD)2.6717578
Skewness2.3988098
Sum3023682.8
Variance48.170814
MonotonicityNot monotonic
2024-01-25T00:05:00.186126image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
8.25300293 3
 
< 0.1%
3.833532715 3
 
< 0.1%
2.605157471 3
 
< 0.1%
5.960540771 3
 
< 0.1%
2.691524658 3
 
< 0.1%
4.440393066 3
 
< 0.1%
2.277757568 3
 
< 0.1%
3.839447021 3
 
< 0.1%
3.452429199 3
 
< 0.1%
3.829333496 3
 
< 0.1%
Other values (383689) 385470
> 99.9%
ValueCountFrequency (%)
-2.207167969 1
< 0.1%
-0.4198376465 1
< 0.1%
-0.2881835938 1
< 0.1%
-0.2373730469 1
< 0.1%
-0.2097723389 1
< 0.1%
-0.2043041992 1
< 0.1%
-0.2032250977 1
< 0.1%
-0.1686035156 1
< 0.1%
-0.1585546875 1
< 0.1%
-0.1330993652 1
< 0.1%
ValueCountFrequency (%)
96.62373596 1
< 0.1%
89.28724976 1
< 0.1%
88.80547852 1
< 0.1%
72.62127136 1
< 0.1%
72.00088806 1
< 0.1%
70.46192139 1
< 0.1%
70.45227844 1
< 0.1%
68.9582666 1
< 0.1%
68.2444397 1
< 0.1%
64.44408203 1
< 0.1%

tmax[9]
Real number (ℝ)

Distinct68376
Distinct (%)17.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean80.758572
Minimum0
Maximum204.6
Zeros231
Zeros (%)0.1%
Negative0
Negative (%)0.0%
Memory size2.9 MiB
2024-01-25T00:05:00.294393image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile25.8
Q171
median71.8
Q372.6
95-th percentile174.8
Maximum204.6
Range204.6
Interquartile range (IQR)1.6

Descriptive statistics

Standard deviation37.492926
Coefficient of variation (CV)0.4642594
Kurtosis2.5498039
Mean80.758572
Median Absolute Deviation (MAD)0.8
Skewness1.39747
Sum31132430
Variance1405.7195
MonotonicityNot monotonic
2024-01-25T00:05:00.400577image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
71.6 21882
 
5.7%
72.2 21857
 
5.7%
71.2 21468
 
5.6%
72 21464
 
5.6%
71.4 20949
 
5.4%
71.8 20646
 
5.4%
72.4 20634
 
5.4%
71 20350
 
5.3%
70.8 16637
 
4.3%
72.6 14044
 
3.6%
Other values (68366) 185569
48.1%
ValueCountFrequency (%)
0 231
0.1%
0.4 250
0.1%
0.6 148
< 0.1%
0.8 151
< 0.1%
1 216
0.1%
1.038630419 1
 
< 0.1%
1.113818966 1
 
< 0.1%
1.129622881 1
 
< 0.1%
1.137838396 1
 
< 0.1%
1.147279992 1
 
< 0.1%
ValueCountFrequency (%)
204.6 108
< 0.1%
204.4 62
< 0.1%
204.2 71
< 0.1%
204 115
< 0.1%
203.8 61
< 0.1%
203.6 48
< 0.1%
203.4 30
 
< 0.1%
203.2 44
 
< 0.1%
203 45
 
< 0.1%
202.9509993 1
 
< 0.1%

rms[9]
Real number (ℝ)

Distinct385498
Distinct (%)> 99.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.377497
Minimum0.29468131
Maximum5.9826448
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.9 MiB
2024-01-25T00:05:00.501696image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/

Quantile statistics

Minimum0.29468131
5-th percentile0.84823478
Q11.1290181
median1.353291
Q31.5986989
95-th percentile1.9880717
Maximum5.9826448
Range5.6879635
Interquartile range (IQR)0.46968089

Descriptive statistics

Standard deviation0.34920756
Coefficient of variation (CV)0.25350876
Kurtosis1.1274859
Mean1.377497
Median Absolute Deviation (MAD)0.23386366
Skewness0.49420762
Sum531025.09
Variance0.12194592
MonotonicityNot monotonic
2024-01-25T00:05:00.608618image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1.436342686 2
 
< 0.1%
0.9744653365 2
 
< 0.1%
0.9712543798 1
 
< 0.1%
1.251719514 1
 
< 0.1%
1.633278339 1
 
< 0.1%
1.509065732 1
 
< 0.1%
1.340873424 1
 
< 0.1%
1.02666082 1
 
< 0.1%
1.410268393 1
 
< 0.1%
1.070344912 1
 
< 0.1%
Other values (385488) 385488
> 99.9%
ValueCountFrequency (%)
0.2946813084 1
< 0.1%
0.3077491914 1
< 0.1%
0.3083188576 1
< 0.1%
0.3453334303 1
< 0.1%
0.3528708014 1
< 0.1%
0.3568653142 1
< 0.1%
0.3573347582 1
< 0.1%
0.3755118256 1
< 0.1%
0.3805453622 1
< 0.1%
0.3822928893 1
< 0.1%
ValueCountFrequency (%)
5.98264481 1
< 0.1%
5.898676796 1
< 0.1%
5.842367749 1
< 0.1%
5.635410718 1
< 0.1%
5.587724079 1
< 0.1%
5.51300246 1
< 0.1%
5.488479668 1
< 0.1%
5.331706397 1
< 0.1%
5.2760714 1
< 0.1%
5.115001233 1
< 0.1%

pmax[10]
Real number (ℝ)

HIGH CORRELATION 

Distinct382366
Distinct (%)99.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean37.827489
Minimum2.5332672
Maximum141.43984
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.9 MiB
2024-01-25T00:05:00.723000image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/

Quantile statistics

Minimum2.5332672
5-th percentile8.0663281
Q113.758305
median23.506975
Q359.20765
95-th percentile98.045552
Maximum141.43984
Range138.90658
Interquartile range (IQR)45.449345

Descriptive statistics

Standard deviation30.010446
Coefficient of variation (CV)0.7933502
Kurtosis-0.20598519
Mean37.827489
Median Absolute Deviation (MAD)13.65278
Skewness0.9500418
Sum14582497
Variance900.62688
MonotonicityNot monotonic
2024-01-25T00:05:00.845060image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
15.76771545 3
 
< 0.1%
52.37387695 3
 
< 0.1%
11.14618835 3
 
< 0.1%
14.68529968 3
 
< 0.1%
15.00384827 3
 
< 0.1%
19.4150116 3
 
< 0.1%
11.57786865 3
 
< 0.1%
17.92897949 3
 
< 0.1%
9.363476562 3
 
< 0.1%
13.17295532 3
 
< 0.1%
Other values (382356) 385470
> 99.9%
ValueCountFrequency (%)
2.533267212 1
< 0.1%
2.575378418 1
< 0.1%
2.616571045 1
< 0.1%
2.640377808 1
< 0.1%
2.646261597 1
< 0.1%
2.656695557 1
< 0.1%
2.657800293 1
< 0.1%
2.685852051 1
< 0.1%
2.788931274 1
< 0.1%
2.832531738 1
< 0.1%
ValueCountFrequency (%)
141.4398438 1
< 0.1%
141.0632538 1
< 0.1%
140.1047791 1
< 0.1%
140.0490845 1
< 0.1%
139.5186493 1
< 0.1%
139.2727783 1
< 0.1%
139.0792267 1
< 0.1%
138.9490479 1
< 0.1%
138.036322 1
< 0.1%
137.9486938 1
< 0.1%

negpmax[10]
Real number (ℝ)

HIGH CORRELATION  SKEWED 

Distinct377679
Distinct (%)98.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean-21.218853
Minimum-57175.302
Maximum-1.2966765
Zeros0
Zeros (%)0.0%
Negative385500
Negative (%)100.0%
Memory size2.9 MiB
2024-01-25T00:05:00.951357image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/

Quantile statistics

Minimum-57175.302
5-th percentile-60.279247
Q1-33.188326
median-10.563461
Q3-5.7266167
95-th percentile-4.2347986
Maximum-1.2966765
Range57174.005
Interquartile range (IQR)27.461709

Descriptive statistics

Standard deviation124.88136
Coefficient of variation (CV)-5.8853963
Kurtosis129964.26
Mean-21.218853
Median Absolute Deviation (MAD)6.1252533
Skewness-330.21972
Sum-8179867.9
Variance15595.354
MonotonicityNot monotonic
2024-01-25T00:05:01.157494image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
-4.910568237 6
 
< 0.1%
-5.054473877 4
 
< 0.1%
-4.543283081 4
 
< 0.1%
-5.980493164 4
 
< 0.1%
-4.317669678 4
 
< 0.1%
-4.803695679 4
 
< 0.1%
-5.529656982 4
 
< 0.1%
-5.207073975 3
 
< 0.1%
-5.707983398 3
 
< 0.1%
-5.794921875 3
 
< 0.1%
Other values (377669) 385461
> 99.9%
ValueCountFrequency (%)
-57175.30155 1
< 0.1%
-27147.56546 1
< 0.1%
-26213.08175 1
< 0.1%
-24132.99234 1
< 0.1%
-19633.52939 1
< 0.1%
-11174.02682 1
< 0.1%
-4868.865443 1
< 0.1%
-3722.032532 1
< 0.1%
-3718.029122 1
< 0.1%
-3640.766743 1
< 0.1%
ValueCountFrequency (%)
-1.296676532 1
< 0.1%
-1.577714845 1
< 0.1%
-1.65885583 1
< 0.1%
-1.688972783 1
< 0.1%
-1.740748263 1
< 0.1%
-1.754078834 1
< 0.1%
-1.829866315 1
< 0.1%
-1.829890932 1
< 0.1%
-1.861529948 1
< 0.1%
-1.862770994 1
< 0.1%

area[10]
Real number (ℝ)

HIGH CORRELATION 

Distinct384809
Distinct (%)99.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20.479499
Minimum0.27023926
Maximum96.005894
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.9 MiB
2024-01-25T00:05:01.264852image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/

Quantile statistics

Minimum0.27023926
5-th percentile5.5611442
Q19.2624475
median14.784152
Q330.412825
95-th percentile47.963302
Maximum96.005894
Range95.735655
Interquartile range (IQR)21.150377

Descriptive statistics

Standard deviation13.938797
Coefficient of variation (CV)0.680622
Kurtosis-0.22840667
Mean20.479499
Median Absolute Deviation (MAD)7.5072791
Skewness0.88584268
Sum7894846.7
Variance194.29007
MonotonicityNot monotonic
2024-01-25T00:05:01.371845image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
10.82665771 3
 
< 0.1%
6.974737549 3
 
< 0.1%
12.30714111 2
 
< 0.1%
8.04086731 2
 
< 0.1%
9.763195801 2
 
< 0.1%
9.513516846 2
 
< 0.1%
20.70158447 2
 
< 0.1%
7.362470703 2
 
< 0.1%
14.78256958 2
 
< 0.1%
9.698127441 2
 
< 0.1%
Other values (384799) 385478
> 99.9%
ValueCountFrequency (%)
0.2702392578 1
< 0.1%
0.5711914062 1
< 0.1%
0.7160888672 1
< 0.1%
0.7771801758 1
< 0.1%
0.8107910156 1
< 0.1%
0.8118481445 1
< 0.1%
0.8753027344 1
< 0.1%
0.9371520996 1
< 0.1%
0.9420947266 1
< 0.1%
0.9578417969 1
< 0.1%
ValueCountFrequency (%)
96.00589417 1
< 0.1%
94.06421021 1
< 0.1%
91.67852905 1
< 0.1%
91.35036011 1
< 0.1%
90.59869019 1
< 0.1%
89.41956543 1
< 0.1%
89.17119019 1
< 0.1%
88.62298218 1
< 0.1%
88.40623657 1
< 0.1%
88.27855835 1
< 0.1%

tmax[10]
Real number (ℝ)

Distinct29840
Distinct (%)7.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean71.874087
Minimum0
Maximum204.6
Zeros4
Zeros (%)< 0.1%
Negative0
Negative (%)0.0%
Memory size2.9 MiB
2024-01-25T00:05:01.476627image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile70.6
Q171
median71.6
Q372
95-th percentile72.529568
Maximum204.6
Range204.6
Interquartile range (IQR)1

Descriptive statistics

Standard deviation6.9380569
Coefficient of variation (CV)0.096530713
Kurtosis196.44437
Mean71.874087
Median Absolute Deviation (MAD)0.54233165
Skewness11.549228
Sum27707461
Variance48.136634
MonotonicityNot monotonic
2024-01-25T00:05:01.579874image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
71.6 36264
9.4%
71.2 35812
9.3%
72 35395
9.2%
71.8 34797
9.0%
71 34679
9.0%
71.4 34625
9.0%
72.2 34411
8.9%
70.8 33450
8.7%
72.4 25100
6.5%
70.6 23151
6.0%
Other values (29830) 57816
15.0%
ValueCountFrequency (%)
0 4
< 0.1%
0.4 8
< 0.1%
0.6 9
< 0.1%
0.8 4
< 0.1%
1 2
 
< 0.1%
1.2 2
 
< 0.1%
1.4 1
 
< 0.1%
1.6 2
 
< 0.1%
1.8 3
 
< 0.1%
2 6
< 0.1%
ValueCountFrequency (%)
204.6 2
 
< 0.1%
204.2 10
< 0.1%
204 2
 
< 0.1%
203.6 3
 
< 0.1%
203.2 1
 
< 0.1%
203 3
 
< 0.1%
202.8 1
 
< 0.1%
202.6 4
 
< 0.1%
202.4 3
 
< 0.1%
202.3592026 1
 
< 0.1%

rms[10]
Real number (ℝ)

Distinct385499
Distinct (%)> 99.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.4088766
Minimum0.32446226
Maximum6.0062168
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.9 MiB
2024-01-25T00:05:01.679705image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/

Quantile statistics

Minimum0.32446226
5-th percentile0.870531
Q11.1554529
median1.383982
Q31.6357786
95-th percentile2.0307397
Maximum6.0062168
Range5.6817545
Interquartile range (IQR)0.48032572

Descriptive statistics

Standard deviation0.35542836
Coefficient of variation (CV)0.25227786
Kurtosis0.78575958
Mean1.4088766
Median Absolute Deviation (MAD)0.23903158
Skewness0.46683317
Sum543121.92
Variance0.12632932
MonotonicityNot monotonic
2024-01-25T00:05:01.784183image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1.403088952 2
 
< 0.1%
1.285425125 1
 
< 0.1%
1.088636365 1
 
< 0.1%
1.141527695 1
 
< 0.1%
1.417580161 1
 
< 0.1%
2.141293065 1
 
< 0.1%
1.567407049 1
 
< 0.1%
1.14740312 1
 
< 0.1%
1.783982091 1
 
< 0.1%
1.082471853 1
 
< 0.1%
Other values (385489) 385489
> 99.9%
ValueCountFrequency (%)
0.3244622558 1
< 0.1%
0.3490767694 1
< 0.1%
0.3564049712 1
< 0.1%
0.3603855233 1
< 0.1%
0.3681912796 1
< 0.1%
0.3787332456 1
< 0.1%
0.3806516496 1
< 0.1%
0.3840345706 1
< 0.1%
0.3847241408 1
< 0.1%
0.3848946673 1
< 0.1%
ValueCountFrequency (%)
6.006216764 1
< 0.1%
5.314943095 1
< 0.1%
5.18903791 1
< 0.1%
5.141877978 1
< 0.1%
5.060894642 1
< 0.1%
5.036771228 1
< 0.1%
4.945917024 1
< 0.1%
4.943960316 1
< 0.1%
4.942416725 1
< 0.1%
4.861858383 1
< 0.1%

pmax[11]
Real number (ℝ)

HIGH CORRELATION 

Distinct380741
Distinct (%)98.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean22.118955
Minimum1.9351257
Maximum134.46443
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.9 MiB
2024-01-25T00:05:01.890782image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/

Quantile statistics

Minimum1.9351257
5-th percentile4.6433621
Q17.9046913
median13.388216
Q326.453506
95-th percentile71.235441
Maximum134.46443
Range132.5293
Interquartile range (IQR)18.548815

Descriptive statistics

Standard deviation21.599092
Coefficient of variation (CV)0.97649698
Kurtosis2.8156799
Mean22.118955
Median Absolute Deviation (MAD)6.8597524
Skewness1.8032011
Sum8526857.1
Variance466.52079
MonotonicityNot monotonic
2024-01-25T00:05:02.005402image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
5.032846069 3
 
< 0.1%
4.698397827 3
 
< 0.1%
13.2072998 3
 
< 0.1%
11.71374207 3
 
< 0.1%
5.396386719 3
 
< 0.1%
19.9479187 3
 
< 0.1%
5.903329468 3
 
< 0.1%
11.76604004 3
 
< 0.1%
5.520040894 3
 
< 0.1%
12.6228241 3
 
< 0.1%
Other values (380731) 385470
> 99.9%
ValueCountFrequency (%)
1.935125732 1
< 0.1%
2.100262451 1
< 0.1%
2.185696411 1
< 0.1%
2.189855957 1
< 0.1%
2.203860474 1
< 0.1%
2.228222656 1
< 0.1%
2.237850952 1
< 0.1%
2.241149902 1
< 0.1%
2.294869995 1
< 0.1%
2.298760986 1
< 0.1%
ValueCountFrequency (%)
134.4644257 1
< 0.1%
133.3981323 1
< 0.1%
133.3880951 1
< 0.1%
131.3401154 1
< 0.1%
130.8017578 1
< 0.1%
130.5105743 1
< 0.1%
130.0271454 1
< 0.1%
129.1365356 1
< 0.1%
128.5394073 1
< 0.1%
128.5250183 1
< 0.1%

negpmax[11]
Real number (ℝ)

HIGH CORRELATION  SKEWED 

Distinct370190
Distinct (%)96.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean-12.59736
Minimum-48053.652
Maximum-0.67691016
Zeros0
Zeros (%)0.0%
Negative385500
Negative (%)100.0%
Memory size2.9 MiB
2024-01-25T00:05:02.121729image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/

Quantile statistics

Minimum-48053.652
5-th percentile-42.678708
Q1-13.61974
median-6.0868957
Q3-4.9193085
95-th percentile-3.9169482
Maximum-0.67691016
Range48052.975
Interquartile range (IQR)8.7004318

Descriptive statistics

Standard deviation101.81297
Coefficient of variation (CV)-8.0820876
Kurtosis156264.56
Mean-12.59736
Median Absolute Deviation (MAD)1.6664492
Skewness-375.08918
Sum-4856282.3
Variance10365.88
MonotonicityNot monotonic
2024-01-25T00:05:02.229774image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
-4.324862671 5
 
< 0.1%
-4.840386963 5
 
< 0.1%
-4.875790405 4
 
< 0.1%
-4.616397095 4
 
< 0.1%
-4.633285522 4
 
< 0.1%
-6.180987549 4
 
< 0.1%
-4.271362305 4
 
< 0.1%
-5.357632446 4
 
< 0.1%
-4.802880859 4
 
< 0.1%
-4.696899414 4
 
< 0.1%
Other values (370180) 385458
> 99.9%
ValueCountFrequency (%)
-48053.65215 1
< 0.1%
-30421.15663 1
< 0.1%
-22899.46005 1
< 0.1%
-11250.94698 1
< 0.1%
-5205.200778 1
< 0.1%
-3653.52956 1
< 0.1%
-1927.327313 1
< 0.1%
-1117.782421 1
< 0.1%
-1082.339312 1
< 0.1%
-966.2279201 1
< 0.1%
ValueCountFrequency (%)
-0.6769101631 1
< 0.1%
-0.7331052367 1
< 0.1%
-1.16586669 1
< 0.1%
-1.203739489 1
< 0.1%
-1.310706983 1
< 0.1%
-1.526378556 1
< 0.1%
-1.537976697 1
< 0.1%
-1.610357947 1
< 0.1%
-1.647279814 1
< 0.1%
-1.679115141 1
< 0.1%

Interactions

2024-01-25T00:04:58.174466image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:04:47.757777image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:04:48.933629image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:04:50.062117image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:04:51.223212image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:04:52.414759image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:04:53.678097image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:04:54.800991image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:04:55.872206image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:04:56.970915image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:04:58.279702image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:04:47.864203image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:04:49.037990image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:04:50.181217image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:04:51.340846image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:04:52.526555image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:04:53.796715image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:04:54.905345image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:04:55.979787image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:04:57.081314image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:04:58.383024image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:04:48.059657image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:04:49.137909image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:04:50.290698image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:04:51.453156image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:04:52.640564image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:04:53.911592image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:04:55.009042image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:04:56.085462image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:04:57.187999image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:04:58.487638image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:04:48.166867image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:04:49.252071image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:04:50.406379image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:04:51.571551image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:04:52.754166image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:04:54.024080image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:04:55.114236image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:04:56.192884image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:04:57.296287image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:04:58.602065image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:04:48.279884image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:04:49.371080image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:04:50.525128image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:04:51.693950image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:04:52.877571image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:04:54.145115image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:04:55.229620image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:04:56.306331image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:04:57.412824image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:04:58.715645image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:04:48.391592image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:04:49.485968image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:04:50.653557image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:04:51.817061image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:04:53.094713image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:04:54.255291image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:04:55.339777image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:04:56.417690image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:04:57.528038image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:04:58.823155image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:04:48.495653image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:04:49.602391image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:04:50.772292image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:04:51.934052image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:04:53.213263image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:04:54.363389image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:04:55.439758image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:04:56.527936image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:04:57.639678image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:04:58.928353image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:04:48.602129image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
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2024-01-25T00:04:50.879907image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:04:52.051973image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:04:53.325465image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:04:54.469656image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:04:55.541388image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:04:56.636986image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:04:57.746710image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:04:59.035007image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:04:48.712505image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:04:49.829740image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:04:50.992186image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:04:52.174292image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:04:53.443610image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:04:54.575863image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:04:55.645624image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:04:56.746347image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:04:57.953201image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:04:59.146664image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:04:48.823446image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:04:49.946832image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:04:51.110175image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:04:52.294153image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:04:53.560838image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:04:54.687672image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:04:55.761633image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:04:56.861865image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
2024-01-25T00:04:58.068674image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/

Correlations

2024-01-25T00:05:02.308288image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
area[10]area[9]negpmax[10]negpmax[11]pmax[10]pmax[11]rms[10]rms[9]tmax[10]tmax[9]
area[10]1.0000.664-0.886-0.2980.9690.460-0.001-0.001-0.200-0.168
area[9]0.6641.000-0.655-0.0250.6720.1430.001-0.001-0.130-0.137
negpmax[10]-0.886-0.6551.0000.317-0.927-0.4450.0000.0020.2030.173
negpmax[11]-0.298-0.0250.3171.000-0.329-0.7640.0020.0040.0780.034
pmax[10]0.9690.672-0.927-0.3291.0000.497-0.001-0.000-0.209-0.173
pmax[11]0.4600.143-0.445-0.7640.4971.000-0.002-0.000-0.106-0.043
rms[10]-0.0010.0010.0000.002-0.001-0.0021.0000.002-0.0010.001
rms[9]-0.001-0.0010.0020.004-0.000-0.0000.0021.000-0.000-0.027
tmax[10]-0.200-0.1300.2030.078-0.209-0.106-0.001-0.0001.0000.449
tmax[9]-0.168-0.1370.1730.034-0.173-0.0430.001-0.0270.4491.000

Missing values

2024-01-25T00:04:59.251845image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
A simple visualization of nullity by column.
2024-01-25T00:04:59.472307image/svg+xmlMatplotlib v3.7.4, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Sample

area[9]tmax[9]rms[9]pmax[10]negpmax[10]area[10]tmax[10]rms[10]pmax[11]negpmax[11]
048.42256772.00.97125442.068393-19.71633623.15281972.01.28542512.438458-18.148151
147.55985770.81.64660638.690210-19.61362320.57432170.81.23641012.326212-5.670920
246.12118971.61.50949940.337067-23.63797019.45694671.61.9738039.253250-4.282883
348.82190672.01.94564437.796774-21.11472520.89789772.01.22452610.900876-5.595096
449.84617171.01.47177142.202023-20.66632421.79563871.01.60449513.956659-5.728705
545.46407671.01.14587743.243845-19.25469120.28160371.02.2186399.516568-6.212802
649.53738171.81.20906341.711472-24.76863121.99812371.81.31412010.503293-5.223541
746.85283972.21.53014440.901083-21.22507623.05915872.21.6784809.434543-5.077420
850.43676971.61.55212142.626450-21.28694222.97186971.61.4746967.110852-5.052600
942.92293170.63.25006638.703922-20.27459420.53868970.61.5544858.898010-6.269320
area[9]tmax[9]rms[9]pmax[10]negpmax[10]area[10]tmax[10]rms[10]pmax[11]negpmax[11]
3854903.25150640.6000001.3669574.524686-5.3543334.85472972.6378121.5447513.828113-6.479626
3854912.239471136.8000001.3938229.499997-4.3179965.17233472.0291251.4503923.132718-5.131808
3854922.196174199.0000001.5271265.463806-4.4943851.84306671.6000001.1254105.023248-4.589545
3854932.62993856.8000001.8351212.997644-6.4184941.135713190.8000001.3605943.868164-5.029148
38549418.59036772.0586561.3967004.505969-5.4512453.950815197.6000001.6355957.740149-3.022403
3854951.71293693.2000000.9062765.018600-4.6417711.71520771.4000001.4679895.526794-6.992345
3854966.68489572.2000001.67567112.100403-4.6642468.12340172.2000001.85640715.208563-5.161127
3854972.33115976.4000001.2679676.587385-3.6482339.38139971.2472741.6551365.343299-4.516763
3854985.84697372.2000001.18176613.214905-4.5228888.46304972.0000001.64712913.605057-5.050461
3854992.189797130.2000001.0629974.959647-21.2462213.00037871.8000001.7616346.934341-15.145020